Response of Container-grown Ninebark to Crude and Nutrient-enriched Recirculating Compost Leachates
Bibliographic record
Abstract
Ninebark [ Physocarpus opulifolius (L.) Maxim] was grown on troughs under greenhouse conditions in 2.5-L containers filled with 100% composted pine bark and fertigated with drip irrigation using the following nutrient solutions: 1) a complete (control) solution, electrical conductivity (EC) of 1.75 dS·m –1 , nonrecirculated; 2) solution as in treatment 1 but recirculated; 3) unamended municipal solid waste compost (MSW) leachate, EC 1.75 dS·m –1 , recirculated; 4) solution as in treatment 3 amended in order of priority with NO 3 -N, NH 4 -N, P, K, Ca and/or Mg, to match the concentrations in the complete solution, EC 2.60 dS·m –1 , recirculated; 5) unamended turkey litter compost (TLC) leachate, EC 1.75 dS·m –1 , recirculated; and 6) solution as in treatment 5 amended as in treatment 4, EC 2.40 dS·m –1 , recirculated. Among the four recirculated compost leachate treatments, shoot (stems and leaves) dry weight of ninebark was least with the unamended MSW, intermediate with amended MSW, and greatest but similar with both unamended and amended TLC. The most growth occurred with the recirculated control solution. Among the four leachate treatments, ninebark grew acceptably well only with recirculated unamended TLC, and was similar to that with the nonrecirculated control solution. Three treatments (nonrecirculated control, recirculated control and unamended TLC) showed no nutrient toxicity or deficiency symptoms. Poorer growth responses in the other treatments (amended TLC, amended MSW and unamended MSW) were related primarily to excess salts and/or nutritional disorders due to imbalance(s) in one or more nutrients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".